precise evidence for specific problems

Behavioral Theory A Primer about concepts and behavior-change techniques

Precise Evidence for Specific Problems@eheklerDr. Eric HeklerArizona State UniversityAugust 4, 2016

The talk will briefly set up the current context for mHealth / UbiComp / digital health research efforts as seen from various disciplinary lenses. Following this, the precision medicine initiative will be discussed followed by a discussion on one subclass of prevention interventions, labeled precision behavior change, which could fit well within the precision medicine initiative. Following the definition of precision behavior change, transdisciplinary research questions, with a particular focus on attempting to articulate intellectual merit and contributions for each discipline when exploring the research questions, will be discussed. The talk will conclude with plausible next steps to spur conversation among the webinar participants and later viewers on ways to refine this transdisciplinary research agenda to see if it is viable and, if so, how best to more actively enable it as an organizing moon shot agenda for the mHealth research community.1

OutlineMotivations & perspective

Precise solutions

Precise evidence

Agile science (v.2)

Citizen-led science & PLM@ehekler

The talk will briefly set up the current context for mHealth / UbiComp / digital health research efforts as seen from various disciplinary lenses. Following this, the precision medicine initiative will be discussed followed by a discussion on one subclass of prevention interventions, labeled precision behavior change, which could fit well within the precision medicine initiative. Following the definition of precision behavior change, transdisciplinary research questions, with a particular focus on attempting to articulate intellectual merit and contributions for each discipline when exploring the research questions, will be discussed. The talk will conclude with plausible next steps to spur conversation among the webinar participants and later viewers on ways to refine this transdisciplinary research agenda to see if it is viable and, if so, how best to more actively enable it as an organizing moon shot agenda for the mHealth research community.

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Motivations & Perspective

Human Genome Project

Walking on the Moon

Penicillin Eric Hekler, @eheklertheamazingworldofgumball.wikia.comhttp://www.genome.gov/

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http://youtu.be/QPKKQnijnsM

Flickr just.Luc

Flickr-meanMrmustard

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Behaviors explain most variability in health Flickr Stuck in Customs@eheklerMcGinnis, et al. 2002 Health Affairs

Behavior at the centerHovell M, Wahlgren D, Adams M. Emerging theories in health promotion practice and research. 2009;2:347-85.@ehekler

Discuss the lack of understanding from behavioral scientists on how to really deal with big data and opportunities for setting up in the wild studies that could later be harnessed for A/B testing. Nice melding of behavioral science knowledge of randomized controlled trials and HCIs knowledge on the systems to automate those types of systems in the real-world.9

Core problem: SkeumorphismsSchueller et al. 2013

Precise Solutions

Personal, pervasive, & powerful technologiesFlickr Stuck in CustomsPatrick, Hekler, Estrin, Godino, Crane, Riper, & Mohr, Riley, Manuscript in Prep

@ehekler

@eheklerhttp://www.nih.gov/precisionmedicine/

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Just in Time Adaptive Interventions@ehekler

Just in time: State of vulnerabilityFlickr - Rob Marquardt

@eheklerNahum-Shani, Hekler, & Spruijt-Metz, (2015) Health Psychology

Based on this, we need to move more into an open discussion in which we explore lots and lots of different ideas if we really want to understand which ones are best.Sadly, science, particularly behavioral science doesnt really have the sort of maker culture that would allow us. As such, a key emphasis. 15

Just in time: State of opportunityFlickr - Miroslav Petrasko

@eheklerNahum-Shani, Hekler, & Spruijt-Metz, (2015) Health Psychology


Just in time: ReceptiveFlickr-Jonathan Powell

Nahum-Shani, Hekler, & Spruijt-Metz, (2015) Health Psychology@ehekler

Adaptive: Series of just in time moments@ehekler

Flickr - Dave Gray

System controlled Giving the fishNSF IIS-1449751: EAGER: Defining a Dynamical Behavioral Model to Support a Just in Time Adaptive Intervention, PIs, Hekler & Rivera@ehekler

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Modeling behavior Riley, Martin, Rivera, Hekler, et al. 2016; Martin, Riley, Rivera, Hekler, et al. 2014

@ehekler

Three Example Individualized Computational Models via Black-Box System ID: Goals-Expected Points-Granted Points model; B: Predicted Busyness; S: Predicted Stress; T: Predicted Typical; W: Weekday-WeekendModeling differences

Future-oriented predictions

Hekler, et al. 2013 Health Education and Behavior@ehekler

Martin, Rivera, & Hekler Manuscript Submitted for Publication

Future-oriented decisions@ehekler


Individual controlled Teaching to fishEric Hekler, Jisoo Lee, Erin Walker, Winslow Burleson, Arizona State University; Bob Evans, Google

Flickr Juhan Sonin@ehekler

NOTE, this current draft is just to get a sense of timing and flow on key points to discuss. Formatting on almost all slides will not remain (e.g., likely will NOT have the titles at the top like that).24

Measure success towards goalResultsSelf-experimentationPlan+Implement for 1 week

@ehekler

- OK, now youre creating a plan for your problem. For a successful plan, you should set an appropriate goal, and come up with ways to apply behavior change techniques.

MS Wearables 101 CourseEmil Chiauzzi, PatientsLikeMeEric Hekler, Arizona State UniversityPronabesh DasMahapatra, PatientsLikeMe

Precise Evidence

Specific Solutionsfor Specific Problems

Design & Engineering

On Average ScienceOn Average Evidencefor General ProblemsKey

Traditional pathway

Emerging pathway

Product

ProcessProfessional-led

Decision Policies we are talking about what this is supposed to do

Citizens= Patients, Providers, and anyone else driven to solve a problem that the individualhas first-hand experience with.

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Traditional pathway

Emerging pathway

Product

ProcessPrecise Evidencefor Specific Problems

Personalization AlgorithmScienceProfessional-led



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Traditional pathway

Emerging pathway

Product


Personalization AlgorithmScienceProfessional-ledCitizen/Patient-led



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Subjectivity matters@eheklerSolving the last mile problem

Requires a damn good designer AND(/OR?) patient empowerment

. Mullainathan S. Solving social problems with a nudge. TEDIndia. 2009. http://www.ted.com/talks/sendhil_mullainathan.

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From on average to algorithms@eheklerFrom generally true to true for me

Requires acknowledging variance

On Average~50%Personalization/Matchmaking~35%Idiosyncratic/Subjective~15%

Professionals still focus on on average science (even, it appears, with many precision medicine efforts)Professionals need to move towards studying the utility of personalization algorithms

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Role of the professional may change@eheklerFrom solving to empowering

Professional can supportEducationTool buildingCommunicationCuration

Professionals need to continually enable more end-user design, engineering, and Science33

Agile Sciencefriko-diamondsdesigns.blogspot.com

HealthFoo, December 2013: https://www.youtube.com/watch?v=wY-stOXqmuw Watch this video on being a thought leader:https://www.youtube.com/watch?v=_ZBKX-6Gz6A

FIND THE VIDEO MAKING FUN OF TED TALKS AND PUT IN A LINK HERE. 34

Agile science productsModules

Computational models

Personalization algorithms@ehekler

Central to agile science is a focus on products that will be immediately useful for non-scientists. 35

ModulesSmallest, meaningful, self-contained,& repurposable

Perfect intervention packageComponentsFlickr - Paul Swansen

Flickr - Benjamin Esham@ehekler

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Modules@eheklerInputsProcessOutput

Proximity sensor module@eheklerInputsiBeaconsPhoneMeta-dataProcessTransform tagged data into a time-stamped db

OutputTime-stamped csv of indoor location

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ModulesAPIs

www.yelp.com

@ehekler


IFTTT

http://www.ifttt.comModulesTemplateswww.ifttt.com@ehekler

Modules

http://www.ifttt.comwww.ifttt.com@ehekler

Computational modelsRiley, Martin, Rivera, Hekler, et al. 2016; Martin, Riley, Rivera, Hekler, et al. 2014

@ehekler

Computational models: OntologiesLarsen, Michie, Hekler, et el. 2016, Journal of Behavioral Medicine@ehekler

Personalization algorithms

www.netflix.com@ehekler


Martin, Rivera, & Hekler Am. Control Conference (2015)

Personalization algorithms@ehekler


Agile Science Process v0.2

@ehekler

Agile ScienceProcess

Ive been calling this alternative process agile science, which Ill jump into briefly here.47

GenerateDesign & engineer specific solutions for specific problems@ehekler

Formative researchDefining a niche

Defining constraints

Generating solutions

IDEO

Niche specification

IDEO: Human-Centered Design Kit

Design constraints

Generating solutions

Stanford d.School, Bootleg Bootcamp

Complexity mappingFinding assumptions

Defining causal pathways

Defining a research agenda

Finding assumptions via simulation

Martin, Rivera, & Hekler (In preparation)

Finding assumptions via simulation

Martin, Rivera, & Hekler (In preparation)

Causal pathwaysAntecedentsBody MovementConsequencesContext (People, place, time)TimescaleYearMonthDayHourMin

Bouts of MVPAMin/day MVPADaily min/day goal of MVPACardiovascular Fitness (vO2)Self-Management SkillsSelf-Identity as an exerciserAtheroscleroticPlaquePrevention

Research agenda

PrototypingTesting hunches

Testing assumptions

Examining feasibility

Amy Luginbill; Samantha Quagliano; Sepideh Zohreh

S=StopM=MoveI= I statement; I can do it!L=Love (positivity)E=ExhaleSMS: If you are stressed today, try one of the following options, Deep breathing, Stretching, get up move around.

MOBILE CAR MAID SERVICESGREEN CLEAN

Prototype 1: S.M.I.L.E.Prototype 2:Facial WavePrototype 3:SMS InterventionPrototype 4:De-stress your carPivotTesting hunches@ehekler

The group studies were where the most interesting things happened. In particular, this was when the groups really took advantage of crummy trials for better understanding when an idea was working.For example, Amy, Sam, and Sepidehs group was trying to reduce stress. They did a lot of empathizing work and looking into the previous literature to find the importance of breathing and stress management techniques. Sadly though, whenever they tested some of their ideas, which included mantras and other ideas to help simple triggers for relaxing, they all failed.This was particularly fascinating because in their initial brainstorming, they really loved their S.M.I.L.E. accronym that they came up with. When they tested it, comparing it to a control, it simply didnt work.They perceived but ultimately found that they needed to pivot and instead ended up focusing on figuring out ways to de-stress a persons environment. So they went and started cleaning cars and got great responses.

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Testing assumptionsJohn Harlow, Erik Johnston, Zoe Yeh@ehekler

Phoenix Proposition 104John Harlow, Erik Johnston, Zoe Yeh@eheklerhttp://movephx.org/get-the-facts/maps/

Examining feasibility

https://www.youtube.com/watch?v=xy9nSnalvPc

EvaluateDetermine the boundary conditions on when, where, for whom, and in what state a tool produces its desired outcome.@ehekler

Linda M. CollinsThe Methodology CenterPenn Statemethodology.psu.edu@ehekler

Thankfully, there has been great movement away from that classic pipeline and particularly the use of a randomized trial of interventions with multiple components in it, to other strategies that are more mirrored on strategies from engineering. Central to this work is a careful understanding of how to develop the evidence around the components of the intervention, with the assumption being htat the components will be more repurposable. SO, for example, Linda Collins has been pioneering the use of fractional factorial study designs to run interventions with multiple components but with a methodology that supports understanding of how the components and how they interact might function. 64

Micro-randomization designSequential, full factorial designs

Randomize intervention component

Each time we might deliver component

Multiple components can be randomized

Randomized 100s or 1000s of timesKlasnja, Hekler, Shiffman, Boruvka, Almirall, Tewari, Murphy, Health Psych, 2015@ehekler

Indeed, my colleagues and I have ben extending this logic to what weve been calling a micor-randomization study, which is atype of factorial design but that is done within a single person. The idea is to randomize intervention componetns with a person at each time when it might help. The design allows multiple of these to work and there is great power on a single person because it is plausible to randomize hundreds and even thousands of times within person. 65

Dynamic hypotheses- sweet spotHekler (PI), Rivera (Co-PI), NSF IIS-1449751

@ehekler

System identification experimentsNSF IIS-1449751: Defining a Dynamical Behavioral Model to Support a Just in Time Adaptive Intervention, PIs, Hekler & Rivera@ehekler

Myc olleauge, Daniel Rivera, and I have been extending this further using methods fromcontrol systems engineering to develop experimental designs that take more advantage of a priori knowledge than the micro-randomization study. In the discussion section, Id be happy to get into details on these experimental designsbut for the focus of this, the main point is to realize that this is a huge shift in the behavioral science community away from ideas like RCTs nad instead towards methods that embrace and map out idiosyncracy.67

CurateEvidence-based insights for match-making of specific solutions to specific problems

@ehekler

Beyond just the difficulty of the complexity of behavior and the behavioral problems we are trying to solve, there are a lot of demands on behavior change technologies themselves and different points that tend to thought about from different disciplines. Indeed, we want behavior change technologies that are evidence-based, cost-effective, personalized, easy to disseminate, promote maintenance, fit into a persons life, and can, hopefully be financially self-sustained in sustaining. As can be seen just from this list, this cant be achieved through the class disciplinary silo model of creation. 69

Ontologies

Larsen, Michie, Hekler et al. in press

Flipping to the second half of this talk now though, in my view, this will only be achieved by carefully building an ecosystem that supports precision behavior change and I think your HealthKit and ResearchKit are great starting points for this. To set up why though, allow me to briefly take a step back and discuss how behavioral scientists like me were told that we were supposed to do our science. 70

Shared test-beds@ehekler


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PatientsLikeMe@ehekler

Research Kit

https://www.apple.com/ios/whats-new/health/

http://researchkit.github.io/

http://sagebase.org/


Pacowww.pacoapp.com@ehekler

Open Humans@ehekler

eEcosphere@eheklerDISCLAIMER: On scientific advisory board w/ equity stakes in the company

Patient-led science @PLM

PLM is a true pioneer (as you know ;)





Traditional pathway

Emerging pathway

Product





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OpenAPS

OpenAPS

End-User design, engineering, & scienceTarget: empowering systematic patient hackingDisease management (e.g., MS sweet spot study)Next gen drugs (e.g., Lithium study v2.0)Next gen medical devices (e.g., OpenAPS)

Courses on patient-led design, engineering & science

End-user programming tools (e.g., Paco) to empower patient-led design, engineering & science


What you get?Insights on the last mile problem

Highly marketable (?)

Strong value back to your patients


Advocating for culture changeTarget: shifting social, ethical, methodological, and regulatory change to embrace patient-led design, engineering, and science

Devise a pathway through the FDAOpenAPS

Build communication pathways between patient-innovators and professionalsOpenAPS





Traditional pathway

Emerging pathway

Product





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Thanks! What can we build together?Dr. Eric Hekler, Arizona State [email protected], @ehekler

TARGET: Precision behavior changeIndividual/User ControlledSystemControlledJust in Time Adaptive InterventionDo-It-Yourself (DIY)Individual/System Balanced ControlSelf-Created BehaviorChange Module Apps@ehekler

Why now? Behavioral meteorologyFlickr-Bart Everson

Patrick, Riley, Estrin, Hekler, Godino, Crane, Riper, & Mohr, Manuscript in Prep@ehekler

Why now? The world needs usFlickr Stuck in Customs

http://youtu.be/QPKKQnijnsM

Flickr just.Luc

Flickr-meanMrmustard

First step@ehekler

Stop building perfect packagesStart building interoperable modulesFlickr - Paul Swansen

Flickr - Benjamin Eshamwww.agilescience.org

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Interoperable systems@ehekler

Lead

Secondary

Secondary

Secondary

Secondary

Secondary


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Interoperable systems

www.openmhealth.org

Ecologically-valid data streams@ehekler

Lead

Secondary

Secondary

Co-Lead


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Turning noise into information

https://ubicomplab.cs.washington.edu/

Data standardization@ehekler

Lead

Co-Lead

Secondary

Secondary

Secondary


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Data standardization

www.openmhealth.org